13 research outputs found
âFunctional Connectivityâ Is a Sensitive Predictor of Epilepsy Diagnosis after the First Seizure
Background: Although epilepsy affects almost 1 % of the world population, diagnosis of this debilitating disease is still difficult. The EEG is an important tool for epilepsy diagnosis and classification, but the sensitivity of interictal epileptiform discharges (IEDs) on the first EEG is only 30â50%. Here we investigate whether using âfunctional connectivity â can improve the diagnostic sensitivity of the first interictal EEG in the diagnosis of epilepsy. Methodology/Principal Findings: Patients were selected from a database with 390 standard EEGs of patients after a first suspected seizure. Patients who were later diagnosed with epilepsy (i.e. $two seizures) were compared to matched nonepilepsy patients (with a minimum follow-up of one year). The synchronization likelihood (SL) was used as an index of functional connectivity of the EEG, and average SL per patient was calculated in seven frequency bands. In total, 114 patients were selected. Fifty-seven patients were diagnosed with epilepsy (20 had IEDs on their EEG) and 57 matched patients had other diagnoses. Epilepsy patients had significantly higher SL in the theta band than non-epilepsy patients. Furthermore, theta band SL proved to be a significant predictor of a diagnosis of epilepsy. When only those epilepsy patients without IEDs were considered (n = 74), theta band SL could predict diagnosis with specificity of 76 % and sensitivity of 62%. Conclusion/Significance: Theta band functional connectivity may be a useful diagnostic tool in diagnosing epilepsy
High frequency oscillations in the intra-operative ECoG to guide epilepsy surgery (âThe HFO Trialâ): study protocol for a randomized controlled trial
Reversibele neurologische uitval jaren na hooggradig glioom: het SMART-syndroom
Survival in patients with high grade glioma has been extended in recent years as a result of more intensive therapy. As a consequence, more late term complications of treatment may be observed. A 69-year-old woman presented at the outpatient department of Neurology with headache and loss of strength in the left arm. She had been treated 7 years previously for a high grade glioma with resection and radiotherapy. One year later she had received chemotherapy for a local recurrence. Since then she was free of complaints. At investigation a left sided hemiparesis was found. As recurrence of the tumour was suspected, MR imaging of the brain was performed, which showed abnormalities suggestive for the so called 'stroke-like migraine attacks after radiotherapy' (SMART) syndrome. The further clinical course, with spontaneous recovery of strength within a few weeks and the regression of the cortical hyperintensity on MRI, confirmed the probable diagnosis. The SMART syndrome is a relatively unknown condition and should be included in the differential diagnosis in patients who present with new complaints long after cerebral radiotherap
Magnetoencephalographic study of hand and foot sensorimotor organization in 325 consecutive patients evaluated for tumor or epilepsy surgery
Objectives: The presence of intracranial lesions or epilepsy may lead to functional reorganization and hemispheric lateralization. We applied a clinical magnetoencephalography (MEG) protocol for the localization of the contralateral and ipsilateral S1 and M1 of the foot and hand in patients with non-lesional epilepsy, stroke, developmental brain injury, traumatic brain injury and brain tumors. We investigated whether differences in activation patterns could be related to underlying pathology.
Methods: Using dipole fitting, we localized the sources underlying sensory and motor evoked magnetic fields (SEFs and MEFs) of both hands and feet following unilateral stimulation of the median nerve (MN) and posterior tibial nerve (PTN) in 325 consecutive patients. The primary motor cortex was localized using beamforming following a self-paced repetitive motor task for each hand and foot.
Results: The success rate for motor and sensory localization for the feet was significantly lower than for the hands (motor_hand 94.6% versus motor_feet 81.8%, p < 0.001; sensory_hand 95.3% versus sensory_feet 76.0%, p < 0.001). MN and PTN stimulation activated 86.6% in the contralateral S1, with ipsilateral activation < 0.5%. Motor cortex activation localized contralaterally in 76.1% (5.2% ipsilateral, 7.6% bilateral and 11.1% failures) of all motor MEG recordings. The ipsilateral motor responses were found in 43 (14%) out of 308 patients with motor recordings (range: 8.3â50%, depending on the underlying pathology), and had a higher occurrence in the foot than in the hand (motor_foot 44.8% versus motor_hand 29.6%, p = 0.031). Ipsilateral motor responses tended to be more frequent in patients with a history of stroke, traumatic brain injury (TBI) or developmental brain lesions (p = 0.063).
Conclusions: MEG localization of sensorimotor cortex activation was more successful for the hand compared to the foot. In patients with neural lesions, there were signs of brain reorganization as measured by more frequent ipsilateral motor cortical activation of the foot in addition to the traditional sensory and motor activation patterns in the contralateral hemisphere. The presence of ipsilateral neural reorganization, especially around the foot motor area, suggests that careful mapping of the hand and foot in both contralateral and ipsilateral hemispheres prior to surgery might minimize postoperative deficits
Patient characteristics epileptic patients without IEDs and matched non-epileptic patients (nâ=â74).
<p>Note. IEDsâ=âinterictal epileptiform discharges, CNSâ=âcentral nervous system.</p
Other diagnoses after first seizure and EEG in non-epileptic patients (nâ=â57).
<p>Other diagnoses after first seizure and EEG in non-epileptic patients (nâ=â57).</p
Mean SLs of epilepsy and non-epilepsy patients in all seven frequency bands.
<p>Note. ** significant difference between patients and controls, p<.001.</p
Patient characteristics (nâ=â114).
<p>Note. ** significant difference (p<.001) between epileptic and non-epileptic patients of total group (nâ=â114), IEDsâ=âinterictal epileptiform discharges, CNSâ=âcentral nervous system.</p
ROC curve of theta band SL as predictor of diagnosis in epilepsy patients without IEDs and their matched non-epilepsy patients (nâ=â74).
<p>ROC curve of theta band SL as predictor of diagnosis in epilepsy patients without IEDs and their matched non-epilepsy patients (nâ=â74).</p